Improving Likert scales one question at a time

Likert scales are one of the most popular scales used on surveys across industries. Lkert scales can be incredibly useful. They can gather a plethora of information on attitudes, behaviors, thoughts, and many more things. Respondents choose from a continuum of response options.

However, when designed poorly, they can result in poor quality data. Below are some tips to make your Likert scales more effective:

The best Likert scales are those with clearly labeled responses and a corresponding numeric response per option. The more clarity, the more likely a respondent is to correctly understand what you are asking.

Carefully assess whether a midpoint response in needed. There are times when a midpoint places a balance to the response options. At these times, a “neutral” response is valuable data. However at other times, a “neutral” response simply isn’t needed.

Avoid using too many responses on the scale. It further complicates the question for respondents. Try to keep response options around five.

Try to keep all questions contained within the survey on the same scale and with consistent labels. This minimizes the time and effort respondents must utilize to process the question. Making the scales consistent will make things as easy as possible for those answering questions. It will also help to reduce fatigue while taking the survey. When all questions are on the same scale, data cleaning and analysis becomes far easier. Using the same scale across years of the same survey allows you to more easily compare across time.

Do you need some assistance designing a survey with effective Likert questions? Ambivista’s Survey Suite allows you to make Likert scales quickly and easily. If you don’t know where to begin, Ambivista can also help you create questions that effectively capture what are you trying to assess.

I was involved in the initial tour of Ambivista, and it is a comprehensive and robust tool that rivals other "big box" cloud and software based survey tools that I have encountered in the past, including Survey Monkey and Inquisite.